{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Define matplotlib defaults\n",
    "plt.rcParams['figure.figsize']        = 8., 6.\n",
    "plt.rcParams['axes.labelsize']        = 18\n",
    "plt.rcParams['axes.titlesize']        = 18\n",
    "plt.rcParams['xtick.top']             = True\n",
    "plt.rcParams['xtick.bottom']          = True\n",
    "plt.rcParams['ytick.left']            = True\n",
    "plt.rcParams['ytick.right']           = True\n",
    "plt.rcParams['xtick.direction']       = 'in'\n",
    "plt.rcParams['ytick.direction']       = 'in'\n",
    "plt.rcParams['xtick.labelsize']       = 14\n",
    "plt.rcParams['ytick.labelsize']       = 14\n",
    "plt.rcParams['xtick.major.pad']       = 6.\n",
    "plt.rcParams['xtick.minor.pad']       = 6.\n",
    "plt.rcParams['ytick.major.pad']       = 6.\n",
    "plt.rcParams['ytick.minor.pad']       = 6.\n",
    "plt.rcParams['xtick.major.size']      = 6. # major tick size in points\n",
    "plt.rcParams['xtick.minor.size']      = 3. # minor tick size in points\n",
    "plt.rcParams['ytick.major.size']      = 6. # major tick size in points\n",
    "plt.rcParams['ytick.minor.size']      = 3. # minor tick size in points\n",
    "plt.rcParams['text.usetex']           = False\n",
    "plt.rcParams['font.family']           = 'serif'\n",
    "plt.rcParams['font.size']             = 18\n",
    "\n",
    "pd.set_option('display.max_columns', None)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "# FFHQ256"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "experiment_prefix = 'FFHQ256'\n",
    "# Load results\n",
    "df = pd.read_csv(f'../data/{experiment_prefix.lower()}.csv')\n",
    "models = df.model.unique().tolist()\n",
    "print(df.shape)\n",
    "df.head()"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "(227, 10)\n"
     ]
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>model</th>\n",
       "      <th>num_correct</th>\n",
       "      <th>err_rt</th>\n",
       "      <th>f_err_rt</th>\n",
       "      <th>r_err_rt</th>\n",
       "      <th>r_ans_rt</th>\n",
       "      <th>resp_time</th>\n",
       "      <th>f_resp_time</th>\n",
       "      <th>r_resp_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>participant_0</td>\n",
       "      <td>efficient-vdvae</td>\n",
       "      <td>189.0</td>\n",
       "      <td>0.055</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.475</td>\n",
       "      <td>434.27</td>\n",
       "      <td>200.18</td>\n",
       "      <td>234.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>participant_1</td>\n",
       "      <td>efficient-vdvae</td>\n",
       "      <td>191.0</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.495</td>\n",
       "      <td>157.49</td>\n",
       "      <td>76.19</td>\n",
       "      <td>81.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>participant_2</td>\n",
       "      <td>efficient-vdvae</td>\n",
       "      <td>178.0</td>\n",
       "      <td>0.110</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.550</td>\n",
       "      <td>165.03</td>\n",
       "      <td>88.07</td>\n",
       "      <td>76.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>participant_3</td>\n",
       "      <td>efficient-vdvae</td>\n",
       "      <td>180.0</td>\n",
       "      <td>0.100</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.540</td>\n",
       "      <td>197.11</td>\n",
       "      <td>91.66</td>\n",
       "      <td>105.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>participant_4</td>\n",
       "      <td>efficient-vdvae</td>\n",
       "      <td>185.0</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.495</td>\n",
       "      <td>198.15</td>\n",
       "      <td>89.89</td>\n",
       "      <td>108.26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              id            model  num_correct  err_rt  f_err_rt  r_err_rt  \\\n",
       "0  participant_0  efficient-vdvae        189.0   0.055      0.03      0.08   \n",
       "1  participant_1  efficient-vdvae        191.0   0.045      0.04      0.05   \n",
       "2  participant_2  efficient-vdvae        178.0   0.110      0.16      0.06   \n",
       "3  participant_3  efficient-vdvae        180.0   0.100      0.14      0.06   \n",
       "4  participant_4  efficient-vdvae        185.0   0.075      0.07      0.08   \n",
       "\n",
       "   r_ans_rt  resp_time  f_resp_time  r_resp_time  \n",
       "0     0.475     434.27       200.18       234.09  \n",
       "1     0.495     157.49        76.19        81.30  \n",
       "2     0.550     165.03        88.07        76.97  \n",
       "3     0.540     197.11        91.66       105.45  \n",
       "4     0.495     198.15        89.89       108.26  "
      ]
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "columns = df.columns.tolist()[3:]\n",
    "df_results = pd.DataFrame(columns=columns)\n",
    "df_results_sem = pd.DataFrame(columns=columns)\n",
    "for j, model in enumerate(models):\n",
    "    model_res = df.loc[df['model'] == model]\n",
    "    df_results.loc[model] = model_res.mean(numeric_only=True)\n",
    "    df_results_sem.loc[model] = model_res.sem(numeric_only=True) # standard error of the mean\n",
    "\n",
    "df_results"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>err_rt</th>\n",
       "      <th>f_err_rt</th>\n",
       "      <th>r_err_rt</th>\n",
       "      <th>r_ans_rt</th>\n",
       "      <th>resp_time</th>\n",
       "      <th>f_resp_time</th>\n",
       "      <th>r_resp_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>efficient-vdvae</th>\n",
       "      <td>0.088400</td>\n",
       "      <td>0.095600</td>\n",
       "      <td>0.081200</td>\n",
       "      <td>0.50720</td>\n",
       "      <td>281.968400</td>\n",
       "      <td>140.758800</td>\n",
       "      <td>141.209200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>insgen</th>\n",
       "      <td>0.255200</td>\n",
       "      <td>0.235600</td>\n",
       "      <td>0.274800</td>\n",
       "      <td>0.48040</td>\n",
       "      <td>325.794400</td>\n",
       "      <td>151.301200</td>\n",
       "      <td>174.492000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ldm</th>\n",
       "      <td>0.186400</td>\n",
       "      <td>0.178000</td>\n",
       "      <td>0.194800</td>\n",
       "      <td>0.49160</td>\n",
       "      <td>428.755600</td>\n",
       "      <td>205.735200</td>\n",
       "      <td>223.021200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>projected-gan</th>\n",
       "      <td>0.120400</td>\n",
       "      <td>0.134000</td>\n",
       "      <td>0.106800</td>\n",
       "      <td>0.51360</td>\n",
       "      <td>318.164800</td>\n",
       "      <td>149.018000</td>\n",
       "      <td>169.147600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stylegan2-ada</th>\n",
       "      <td>0.215400</td>\n",
       "      <td>0.215600</td>\n",
       "      <td>0.215200</td>\n",
       "      <td>0.50020</td>\n",
       "      <td>358.502800</td>\n",
       "      <td>168.663200</td>\n",
       "      <td>189.839200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stylegan-xl</th>\n",
       "      <td>0.160400</td>\n",
       "      <td>0.158000</td>\n",
       "      <td>0.162800</td>\n",
       "      <td>0.49760</td>\n",
       "      <td>340.209200</td>\n",
       "      <td>150.212800</td>\n",
       "      <td>189.994800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stylenat</th>\n",
       "      <td>0.298600</td>\n",
       "      <td>0.283200</td>\n",
       "      <td>0.314000</td>\n",
       "      <td>0.48460</td>\n",
       "      <td>386.877600</td>\n",
       "      <td>183.340800</td>\n",
       "      <td>203.537600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>styleswin</th>\n",
       "      <td>0.179600</td>\n",
       "      <td>0.160800</td>\n",
       "      <td>0.198400</td>\n",
       "      <td>0.48120</td>\n",
       "      <td>287.758400</td>\n",
       "      <td>135.370800</td>\n",
       "      <td>152.387600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unleashing</th>\n",
       "      <td>0.172593</td>\n",
       "      <td>0.202963</td>\n",
       "      <td>0.142222</td>\n",
       "      <td>0.53037</td>\n",
       "      <td>329.598519</td>\n",
       "      <td>153.707407</td>\n",
       "      <td>175.891481</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   err_rt  f_err_rt  r_err_rt  r_ans_rt   resp_time  \\\n",
       "efficient-vdvae  0.088400  0.095600  0.081200   0.50720  281.968400   \n",
       "insgen           0.255200  0.235600  0.274800   0.48040  325.794400   \n",
       "ldm              0.186400  0.178000  0.194800   0.49160  428.755600   \n",
       "projected-gan    0.120400  0.134000  0.106800   0.51360  318.164800   \n",
       "stylegan2-ada    0.215400  0.215600  0.215200   0.50020  358.502800   \n",
       "stylegan-xl      0.160400  0.158000  0.162800   0.49760  340.209200   \n",
       "stylenat         0.298600  0.283200  0.314000   0.48460  386.877600   \n",
       "styleswin        0.179600  0.160800  0.198400   0.48120  287.758400   \n",
       "unleashing       0.172593  0.202963  0.142222   0.53037  329.598519   \n",
       "\n",
       "                 f_resp_time  r_resp_time  \n",
       "efficient-vdvae   140.758800   141.209200  \n",
       "insgen            151.301200   174.492000  \n",
       "ldm               205.735200   223.021200  \n",
       "projected-gan     149.018000   169.147600  \n",
       "stylegan2-ada     168.663200   189.839200  \n",
       "stylegan-xl       150.212800   189.994800  \n",
       "stylenat          183.340800   203.537600  \n",
       "styleswin         135.370800   152.387600  \n",
       "unleashing        153.707407   175.891481  "
      ]
     },
     "metadata": {},
     "execution_count": 3
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "source": [
    "df_results_sem"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>err_rt</th>\n",
       "      <th>f_err_rt</th>\n",
       "      <th>r_err_rt</th>\n",
       "      <th>r_ans_rt</th>\n",
       "      <th>resp_time</th>\n",
       "      <th>f_resp_time</th>\n",
       "      <th>r_resp_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>efficient-vdvae</th>\n",
       "      <td>0.009664</td>\n",
       "      <td>0.009901</td>\n",
       "      <td>0.012914</td>\n",
       "      <td>0.006246</td>\n",
       "      <td>21.192406</td>\n",
       "      <td>11.390424</td>\n",
       "      <td>11.417181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>insgen</th>\n",
       "      <td>0.017601</td>\n",
       "      <td>0.016473</td>\n",
       "      <td>0.024733</td>\n",
       "      <td>0.011478</td>\n",
       "      <td>23.777574</td>\n",
       "      <td>10.663910</td>\n",
       "      <td>13.574457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ldm</th>\n",
       "      <td>0.016489</td>\n",
       "      <td>0.021772</td>\n",
       "      <td>0.016167</td>\n",
       "      <td>0.009788</td>\n",
       "      <td>55.230255</td>\n",
       "      <td>31.712953</td>\n",
       "      <td>24.802889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>projected-gan</th>\n",
       "      <td>0.012359</td>\n",
       "      <td>0.018257</td>\n",
       "      <td>0.011441</td>\n",
       "      <td>0.008909</td>\n",
       "      <td>28.410436</td>\n",
       "      <td>13.099294</td>\n",
       "      <td>17.466256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stylegan2-ada</th>\n",
       "      <td>0.016593</td>\n",
       "      <td>0.021056</td>\n",
       "      <td>0.019280</td>\n",
       "      <td>0.011498</td>\n",
       "      <td>39.876660</td>\n",
       "      <td>19.352118</td>\n",
       "      <td>20.783225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stylegan-xl</th>\n",
       "      <td>0.011633</td>\n",
       "      <td>0.021370</td>\n",
       "      <td>0.008114</td>\n",
       "      <td>0.011222</td>\n",
       "      <td>33.133068</td>\n",
       "      <td>15.977982</td>\n",
       "      <td>25.494670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stylenat</th>\n",
       "      <td>0.018738</td>\n",
       "      <td>0.022306</td>\n",
       "      <td>0.023345</td>\n",
       "      <td>0.013045</td>\n",
       "      <td>33.772931</td>\n",
       "      <td>15.968820</td>\n",
       "      <td>18.699738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>styleswin</th>\n",
       "      <td>0.011913</td>\n",
       "      <td>0.010407</td>\n",
       "      <td>0.023084</td>\n",
       "      <td>0.013367</td>\n",
       "      <td>24.691156</td>\n",
       "      <td>10.567024</td>\n",
       "      <td>14.558143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unleashing</th>\n",
       "      <td>0.014621</td>\n",
       "      <td>0.021844</td>\n",
       "      <td>0.015232</td>\n",
       "      <td>0.011866</td>\n",
       "      <td>27.981263</td>\n",
       "      <td>12.376047</td>\n",
       "      <td>17.363162</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   err_rt  f_err_rt  r_err_rt  r_ans_rt  resp_time  \\\n",
       "efficient-vdvae  0.009664  0.009901  0.012914  0.006246  21.192406   \n",
       "insgen           0.017601  0.016473  0.024733  0.011478  23.777574   \n",
       "ldm              0.016489  0.021772  0.016167  0.009788  55.230255   \n",
       "projected-gan    0.012359  0.018257  0.011441  0.008909  28.410436   \n",
       "stylegan2-ada    0.016593  0.021056  0.019280  0.011498  39.876660   \n",
       "stylegan-xl      0.011633  0.021370  0.008114  0.011222  33.133068   \n",
       "stylenat         0.018738  0.022306  0.023345  0.013045  33.772931   \n",
       "styleswin        0.011913  0.010407  0.023084  0.013367  24.691156   \n",
       "unleashing       0.014621  0.021844  0.015232  0.011866  27.981263   \n",
       "\n",
       "                 f_resp_time  r_resp_time  \n",
       "efficient-vdvae    11.390424    11.417181  \n",
       "insgen             10.663910    13.574457  \n",
       "ldm                31.712953    24.802889  \n",
       "projected-gan      13.099294    17.466256  \n",
       "stylegan2-ada      19.352118    20.783225  \n",
       "stylegan-xl        15.977982    25.494670  \n",
       "stylenat           15.968820    18.699738  \n",
       "styleswin          10.567024    14.558143  \n",
       "unleashing         12.376047    17.363162  "
      ]
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "plt.errorbar(df_results.index, df_results.err_rt, yerr=df_results_sem.err_rt, fmt='o', capsize=5)\n",
    "plt.ylabel(\"Error Rate\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(experiment_prefix.upper())\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'../plots/{experiment_prefix}_err_rt.png', bbox_inches=None, pad_inches=0.0)\n",
    "\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "plt.errorbar(df_results.index, df_results.f_err_rt, yerr=df_results_sem.f_err_rt, fmt='o', capsize=5)\n",
    "plt.ylabel(\"Error Rate on Fakes\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(experiment_prefix)\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'../plots/{experiment_prefix}_f_err_rt.png', bbox_inches=None, pad_inches=0.0)\n",
    "\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "plt.errorbar(df_results.index, df_results.r_err_rt, yerr=df_results_sem.r_err_rt, fmt='o', capsize=5)\n",
    "plt.ylabel(\"Error Rate on Reals\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.title(experiment_prefix)\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'../plots/{experiment_prefix}_r_err_rt.png', bbox_inches=None, pad_inches=0.0)\n",
    "\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  }
 ],
 "metadata": {
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.10.9 64-bit ('fd-ssl': conda)"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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